Evidence map›Paper›PMID 29741576›Full record

ArticleAmerican journal of epidemiology2018

Cluster-Randomized Test-Negative Design Trials: A Novel and Efficient Method to Assess the Efficacy of Community-Level Dengue Interventions.

Katherine L Anders, Zoe Cutcher, Immo Kleinschmidt, Christl A Donnelly, Neil M Ferguson, Citra Indriani, Peter A Ryan, Scott L O'Neill, Nicholas P Jewell, Cameron P Simmons

Abstract readClinical Trial Protocol
In one paragraph

Article in American journal of epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Programmatic Effectiveness of a Pediatric Typhoid Conjugate Vaccine Campaign in Navi Mumbai, India.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Trial
  7. Efficacy of a spatial repellent for control ofProceedings of the National Academy of Sciences of the United States of America · 2022
    Trial
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  10. Article
  11. Article
  12. Review
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  17. Temporal Confounding in the Test-Negative Design.American journal of epidemiology · 2020
    Article
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  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Katherine L AndersInstitute of Vector-Borne Disease, Monash University, Melbourne, Australia.
Zoe CutcherInstitute of Vector-Borne Disease, Monash University, Melbourne, Australia.
Immo KleinschmidtMRC Tropical Epidemiology Group, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Christl A DonnellyMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Neil M FergusonMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Citra IndrianiCentre for Tropical Medicine, Faculty of Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Peter A RyanInstitute of Vector-Borne Disease, Monash University, Melbourne, Australia.
Scott L O'NeillInstitute of Vector-Borne Disease, Monash University, Melbourne, Australia.
Nicholas P JewellDepartment of Statistics, School of Public Health, University of California, Berkeley, Berkeley, California.
Cameron P SimmonsInstitute of Vector-Borne Disease, Monash University, Melbourne, Australia.

Funding

Statistical Design and Analysis of Cluster Randomized Test-Negative Designs: Studies to Eliminate Dengue FeverR56AI134724 · NIAID · UNIVERSITY OF CALIFORNIA BERKELEY · PI JEWELL, NICHOLAS P · 2018 to 2018
$187k
Medical Research Council MR/K012126/1Medical Research Council MR/R015600/1NIAID NIH HHS R56 AI134724Wellcome Trust
6 · The paper itself

Abstract

Cluster-randomized controlled trials are the gold standard for assessing efficacy of community-level interventions, such as vector-control strategies against dengue. We describe a novel cluster-randomized trial methodology with a test-negative design (CR-TND), which offers advantages over traditional approaches. This method uses outcome-based sampling of patients presenting with a syndrome consistent with the disease of interest, who are subsequently classified as test-positive cases or test-negative controls on the basis of diagnostic testing. We used simulations of a cluster trial to demonstrate validity of efficacy estimates under the test-negative approach. We demonstrated that, provided study arms are balanced for both test-negative and test-positive illness at baseline and that other test-negative design assumptions are met, the efficacy estimates closely match true efficacy. Analytical considerations for an odds ratio-based effect estimate arising from clustered data and potential approaches to analysis are also discussed briefly. We concluded that application of the test-negative design to certain cluster-randomized trials could increase their efficiency and ease of implementation.

Indexed as

Research DesignDengueHumansRandomized Controlled Trials as Topic

Identifiers

PMID29741576
PMCPMC6118074

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.